Validated model and study of a rammed earth wall building

A 2100 m² (GFA) two-storey rammed earth building was built on the Thurgoona campus of Charles Sturt University in 1999. The building is novel both in the use of materials and equipment for heating and cooling. The climate at Wodonga can be characterised as hot and dry, so the challenge of providing comfortable working conditions with minimal energy consumption is considerable. This paper describes a thermal model of one of the second-storey offices on the west-end of the building. The simulation software, TRNSYS, has been used to predict office temperatures and comparisons are made between these and measurements made over a typical week in summer. Reasonable agreement has been achieved under most conditions. The model has been used to investigate key building parameters and strategies, including night flushing, to improve the thermal comfort in the office.

Measurement invariance of English and French Health Education Impact Questionnaire (heiQ) empowerment scales validated for cancer

PURPOSE: If measurement invariance (MI) is demonstrated for a scale completed by respondents from two different language groups, it means that the scale measures the same construct in the same way in both groups. We assessed MI of the French- and English-language versions of the five Health Education Impact Questionnaire (heiQ) empowerment scales validated for the cancer setting. METHODS: Data came from two cross-sectional studies of Canadian cancer survivors (704 English, 520 French). Single-group confirmatory factor analysis (CFA) was used to test whether the hypothesized factor structure of the French-language heiQ empowerment scales fit the data. Multi-group CFAs were conducted to assess different levels of MI conditions (configural, metric, scalar, strict, as well as MI of factor variances, covariances, and latent means) of the French- and English-language heiQ empowerment scales. RESULTS: The correlated five-factor model showed good fit in both language groups (goodness-of-fit indices: CFI ≥ .97; RMSEA ≤ .07). Goodness-of-fit indices and tests of differences in fit between models supported MI of the five-factor model across the two language groups (∆CFI ≤ -.010 combined with ∆RMSEA ≤ .015). CONCLUSIONS: The French- and English-language heiQ empowerment scales measure the same five dimensions of empowerment in the same way across both language groups. Thus, any observed similarities or differences between French- and English-speaking respondents completing these scales are valid and reflect similarities or differences in empowerment across language groups, not measurement artifact. Consequently, heiQ empowerment data from English- and French-speaking respondents can be directly pooled or contrasted in data analyses.

Dive characteristics can predict foraging success in Australian fur seals (arctocephalus pusillus doriferus) as validated by animal-borne video

Dive characteristics and dive shape are often used to infer foraging success in pinnipeds. However, these inferences have not been directly validated in the field with video, and it remains unclear if this method can be applied to benthic foraging animals. This study assessed the ability of dive characteristics from time-depth recorders (TDR) to predict attempted prey capture events (APC) that were directly observed on animal-borne video in Australian fur seals (Arctocephalus pusillus doriferus, n=11). The most parsimonious model predicting the probability of a dive with ≥1 APC on video included only descent rate as a predictor variable. The majority (94%) of the 389 total APC were successful, and the majority of the dives (68%) contained at least one successful APC. The best model predicting these successful dives included descent rate as a predictor. Comparisons of the TDR model predictions to video yielded a maximum accuracy of 77.5% in classifying dives as either APC or non-APC or 77.1% in classifying dives as successful verses unsuccessful. Foraging intensity, measured as either total APC per dive or total successful APC per dive, was best predicted by bottom duration and ascent rate. The accuracy in predicting total APC per dive varied based on the number of APC per dive with maximum accuracy occurring at 1 APC for both total (54%) and only successful APC (52%). Results from this study linking verified foraging dives to dive characteristics potentially opens the door to decades of historical TDR datasets across several otariid species.